AI Medical Compendium Topic

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Endothelial Cells

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HIV is associated with endothelial activation despite ART, in a sub-Saharan African setting.

Neurology(R) neuroimmunology & neuroinflammation
OBJECTIVE: To study the relationship between endothelial dysfunction, HIV infection, and stroke in Malawians.

High-dose atorvastatin versus moderate dose on early vascular protection after ST-elevation myocardial infarction.

Drug design, development and therapy
BACKGROUND AND AIM: Clinical benefits of early high-dose statin therapy after acute coronary syndromes are widely known; however, there is poor evidence on the specific setting of ST-elevation myocardial infarction (STEMI) and dose-dependent effects ...

Calli Essential Oils Synergize with Lawsone against Multidrug Resistant Pathogens.

Molecules (Basel, Switzerland)
The fast development of multi-drug resistant (MDR) organisms increasingly threatens global health and well-being. Plant natural products have been known for centuries as alternative medicines that can possess pharmacological characteristics, includin...

Interactive phenotyping of large-scale histology imaging data with HistomicsML.

Scientific reports
Whole-slide imaging of histologic sections captures tissue microenvironments and cytologic details in expansive high-resolution images. These images can be mined to extract quantitative features that describe tissues, yielding measurements for hundre...

Segmentation of corneal endothelium images using a U-Net-based convolutional neural network.

Artificial intelligence in medicine
Diagnostic information regarding the health status of the corneal endothelium may be obtained by analyzing the size and the shape of the endothelial cells in specular microscopy images. Prior to the analysis, the endothelial cells need to be extracte...

Automated Deep Learning-Based System to Identify Endothelial Cells Derived from Induced Pluripotent Stem Cells.

Stem cell reports
Deep learning technology is rapidly advancing and is now used to solve complex problems. Here, we used deep learning in convolutional neural networks to establish an automated method to identify endothelial cells derived from induced pluripotent stem...

Deep learning enables cross-modality super-resolution in fluorescence microscopy.

Nature methods
We present deep-learning-enabled super-resolution across different fluorescence microscopy modalities. This data-driven approach does not require numerical modeling of the imaging process or the estimation of a point-spread-function, and is based on ...

Blood Brain Barrier Permeability Prediction Using Machine Learning Techniques: An Update.

Current pharmaceutical biotechnology
Blood Brain Barrier (BBB) is the collection of vessels of blood with special properties of permeability that allow a limited range of drug and compounds to pass through it. The BBB plays a vital role in maintaining balance between intracellular and e...

Reinforcement learning-based control of tumor growth under anti-angiogenic therapy.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: In recent decades, cancer has become one of the most fatal and destructive diseases which is threatening humans life. Accordingly, different types of cancer treatment are studied with the main aim to have the best treatment...

Automated segmentation of the corneal endothelium in a large set of 'real-world' specular microscopy images using the U-Net architecture.

Scientific reports
Monitoring the density of corneal endothelial cells (CEC) is essential in the management of corneal diseases. Its manual calculation is time consuming and prone to errors. U-Net, a neural network for biomedical image segmentation, has shown promising...